Objectives: In this study, we measured the extent of ten levels of classified symptoms by 300 (male and female) patients visiting the hair loss clinics of "S" hospitals in Gangbuk and Gangnam between January 2009 and June 2011 by analyzing the patients' chief complaints.
Methods: The method of measurement was based on a symptom questionnaire possessing 51 categories. Through the statistical analysis of data mining techniques, decision trees, and logistic regression, we derived a logistic regression model and decision tree model that improved both the response rate and significant hair loss-related characteristics of the questionnaire.
Results: The results of this study indicate that dry hair, seborrheic scalps and skin, tobacco and/or coffee addiction, anxiety, nausea, indigestion, and facial flushing correlate to hair loss.
Conclusions: We anticipate that the subjective symptoms of hair loss can provide a foundation for preventing secondary diseases and provide clinical data information during the period of treatment. This can contribute to the improvement of patient satisfaction after customized treatment.
Keywords: Alopecia; Decision Trees; Questionnaires; Regression; Signs and Symptoms.